Overview

Dataset statistics

Number of variables20
Number of observations45346
Missing cells9837
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 MiB
Average record size in memory160.0 B

Variable types

Numeric9
Text9
DateTime1
Categorical1

Alerts

status is highly imbalanced (96.6%)Imbalance
spoken_languagesname has 3891 (8.6%) missing valuesMissing
genresname has 2384 (5.3%) missing valuesMissing
director has 836 (1.8%) missing valuesMissing
actor has 2474 (5.5%) missing valuesMissing
popularity is highly skewed (γ1 = 29.21542294)Skewed
return is highly skewed (γ1 = 138.283787)Skewed
id has unique valuesUnique
budget has 36470 (80.4%) zerosZeros
revenue has 37949 (83.7%) zerosZeros
vote_average has 2944 (6.5%) zerosZeros
vote_count has 2846 (6.3%) zerosZeros
runtime has 1535 (3.4%) zerosZeros
return has 39971 (88.1%) zerosZeros

Reproduction

Analysis started2024-07-05 23:16:42.073709
Analysis finished2024-07-05 23:16:49.326826
Duration7.25 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

id
Real number (ℝ)

UNIQUE 

Distinct45346
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108042.22
Minimum2
Maximum469172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:49.364303image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5340.25
Q126390.25
median59852.5
Q3156601.5
95-th percentile357370.75
Maximum469172
Range469170
Interquartile range (IQR)130211.25

Descriptive statistics

Standard deviation112187.33
Coefficient of variation (CV)1.0383656
Kurtosis0.55836782
Mean108042.22
Median Absolute Deviation (MAD)44405
Skewness1.2828454
Sum4.8992825 × 109
Variance1.2585996 × 1010
MonotonicityNot monotonic
2024-07-05T20:16:49.415957image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 1
 
< 0.1%
41939 1
 
< 0.1%
41962 1
 
< 0.1%
41963 1
 
< 0.1%
419639 1
 
< 0.1%
41965 1
 
< 0.1%
41966 1
 
< 0.1%
41967 1
 
< 0.1%
41968 1
 
< 0.1%
41969 1
 
< 0.1%
Other values (45336) 45336
> 99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
ValueCountFrequency (%)
469172 1
< 0.1%
468707 1
< 0.1%
468343 1
< 0.1%
467731 1
< 0.1%
465044 1
< 0.1%
464819 1
< 0.1%
464207 1
< 0.1%
464111 1
< 0.1%
463906 1
< 0.1%
463800 1
< 0.1%

spoken_languagesname
Text

MISSING 

Distinct1501
Distinct (%)3.6%
Missing3891
Missing (%)8.6%
Memory size354.4 KiB
2024-07-05T20:16:49.510170image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length171
Median length7
Mean length9.3983597
Min length3

Characters and Unicode

Total characters389609
Distinct characters171
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique992 ?
Unique (%)2.4%

Sample

1st rowEnglish
2nd rowEspañol
3rd rowEnglish
4th rowEnglish
5th rowDeutsch
ValueCountFrequency (%)
english 28711
52.7%
français 4191
 
7.7%
deutsch 2623
 
4.8%
español 2412
 
4.4%
italiano 2365
 
4.3%
日本語 1756
 
3.2%
pусский 1562
 
2.9%
831
 
1.5%
普通话 790
 
1.4%
हिन्दी 706
 
1.3%
Other values (69) 8557
 
15.7%
2024-07-05T20:16:49.683762image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 42241
10.8%
n 37438
 
9.6%
i 37085
 
9.5%
l 34612
 
8.9%
h 31440
 
8.1%
E 31180
 
8.0%
g 30395
 
7.8%
a 18936
 
4.9%
13059
 
3.4%
, 11646
 
3.0%
Other values (161) 101577
26.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 389609
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 42241
10.8%
n 37438
 
9.6%
i 37085
 
9.5%
l 34612
 
8.9%
h 31440
 
8.1%
E 31180
 
8.0%
g 30395
 
7.8%
a 18936
 
4.9%
13059
 
3.4%
, 11646
 
3.0%
Other values (161) 101577
26.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 389609
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 42241
10.8%
n 37438
 
9.6%
i 37085
 
9.5%
l 34612
 
8.9%
h 31440
 
8.1%
E 31180
 
8.0%
g 30395
 
7.8%
a 18936
 
4.9%
13059
 
3.4%
, 11646
 
3.0%
Other values (161) 101577
26.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 389609
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 42241
10.8%
n 37438
 
9.6%
i 37085
 
9.5%
l 34612
 
8.9%
h 31440
 
8.1%
E 31180
 
8.0%
g 30395
 
7.8%
a 18936
 
4.9%
13059
 
3.4%
, 11646
 
3.0%
Other values (161) 101577
26.1%

genresname
Text

MISSING 

Distinct2255
Distinct (%)5.2%
Missing2384
Missing (%)5.3%
Memory size354.4 KiB
2024-07-05T20:16:49.855174image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length80
Median length65
Mean length16.459243
Min length3

Characters and Unicode

Total characters707122
Distinct characters30
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1076 ?
Unique (%)2.5%

Sample

1st rowComedy, Crime
2nd rowComedy, Drama
3rd rowComedy, Science Fiction
4th rowWar, Drama
5th rowDrama
ValueCountFrequency (%)
drama 20234
21.4%
comedy 13175
13.9%
thriller 7614
 
8.0%
romance 6728
 
7.1%
action 6588
 
7.0%
horror 4668
 
4.9%
crime 4302
 
4.5%
documentary 3919
 
4.1%
adventure 3488
 
3.7%
fiction 3037
 
3.2%
Other values (12) 21006
22.2%
2024-07-05T20:16:50.004176image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 69015
 
9.8%
a 61748
 
8.7%
e 55716
 
7.9%
m 53051
 
7.5%
51797
 
7.3%
o 48491
 
6.9%
, 47995
 
6.8%
i 39613
 
5.6%
n 35622
 
5.0%
y 28487
 
4.0%
Other values (20) 215587
30.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 707122
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 69015
 
9.8%
a 61748
 
8.7%
e 55716
 
7.9%
m 53051
 
7.5%
51797
 
7.3%
o 48491
 
6.9%
, 47995
 
6.8%
i 39613
 
5.6%
n 35622
 
5.0%
y 28487
 
4.0%
Other values (20) 215587
30.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 707122
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 69015
 
9.8%
a 61748
 
8.7%
e 55716
 
7.9%
m 53051
 
7.5%
51797
 
7.3%
o 48491
 
6.9%
, 47995
 
6.8%
i 39613
 
5.6%
n 35622
 
5.0%
y 28487
 
4.0%
Other values (20) 215587
30.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 707122
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 69015
 
9.8%
a 61748
 
8.7%
e 55716
 
7.9%
m 53051
 
7.5%
51797
 
7.3%
o 48491
 
6.9%
, 47995
 
6.8%
i 39613
 
5.6%
n 35622
 
5.0%
y 28487
 
4.0%
Other values (20) 215587
30.5%

title
Text

Distinct42196
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:50.175461image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length105
Median length79
Mean length16.702289
Min length1

Characters and Unicode

Total characters757382
Distinct characters287
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39892 ?
Unique (%)88.0%

Sample

1st rowLock, Stock and Two Smoking Barrels
2nd rowLa estrategia del caracol
3rd rowYoung Einstein
4th rowFlight Command
5th rowHounded
ValueCountFrequency (%)
the 14544
 
10.7%
of 4923
 
3.6%
a 2238
 
1.6%
in 1693
 
1.2%
and 1629
 
1.2%
to 1053
 
0.8%
756
 
0.6%
man 665
 
0.5%
love 664
 
0.5%
for 601
 
0.4%
Other values (24353) 107329
78.9%
2024-07-05T20:16:50.450302image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90771
 
12.0%
e 76195
 
10.1%
a 48911
 
6.5%
o 45636
 
6.0%
n 40797
 
5.4%
r 39993
 
5.3%
i 39748
 
5.2%
t 36706
 
4.8%
s 29500
 
3.9%
h 28499
 
3.8%
Other values (277) 280626
37.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 757382
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
90771
 
12.0%
e 76195
 
10.1%
a 48911
 
6.5%
o 45636
 
6.0%
n 40797
 
5.4%
r 39993
 
5.3%
i 39748
 
5.2%
t 36706
 
4.8%
s 29500
 
3.9%
h 28499
 
3.8%
Other values (277) 280626
37.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 757382
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
90771
 
12.0%
e 76195
 
10.1%
a 48911
 
6.5%
o 45636
 
6.0%
n 40797
 
5.4%
r 39993
 
5.3%
i 39748
 
5.2%
t 36706
 
4.8%
s 29500
 
3.9%
h 28499
 
3.8%
Other values (277) 280626
37.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 757382
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
90771
 
12.0%
e 76195
 
10.1%
a 48911
 
6.5%
o 45636
 
6.0%
n 40797
 
5.4%
r 39993
 
5.3%
i 39748
 
5.2%
t 36706
 
4.8%
s 29500
 
3.9%
h 28499
 
3.8%
Other values (277) 280626
37.1%

budget
Real number (ℝ)

ZEROS 

Distinct1223
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4232579.8
Minimum0
Maximum3.8 × 108
Zeros36470
Zeros (%)80.4%
Negative0
Negative (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:50.526367image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile25000000
Maximum3.8 × 108
Range3.8 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation17443731
Coefficient of variation (CV)4.1213
Kurtosis66.618217
Mean4232579.8
Median Absolute Deviation (MAD)0
Skewness7.1180066
Sum1.9193056 × 1011
Variance3.0428374 × 1014
MonotonicityNot monotonic
2024-07-05T20:16:50.579078image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36470
80.4%
5000000 286
 
0.6%
10000000 258
 
0.6%
20000000 243
 
0.5%
2000000 242
 
0.5%
15000000 226
 
0.5%
3000000 223
 
0.5%
25000000 206
 
0.5%
1000000 197
 
0.4%
30000000 189
 
0.4%
Other values (1213) 6806
 
15.0%
ValueCountFrequency (%)
0 36470
80.4%
1 25
 
0.1%
2 14
 
< 0.1%
3 9
 
< 0.1%
4 7
 
< 0.1%
5 8
 
< 0.1%
6 5
 
< 0.1%
7 4
 
< 0.1%
8 5
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
380000000 1
 
< 0.1%
300000000 1
 
< 0.1%
280000000 1
 
< 0.1%
270000000 1
 
< 0.1%
260000000 3
 
< 0.1%
258000000 1
 
< 0.1%
255000000 1
 
< 0.1%
250000000 10
< 0.1%
245000000 2
 
< 0.1%
237000000 1
 
< 0.1%

revenue
Real number (ℝ)

ZEROS 

Distinct6863
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11233655
Minimum0
Maximum2.7879651 × 109
Zeros37949
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:50.630254image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile48025328
Maximum2.7879651 × 109
Range2.7879651 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation64409896
Coefficient of variation (CV)5.7336544
Kurtosis236.93621
Mean11233655
Median Absolute Deviation (MAD)0
Skewness12.251264
Sum5.0940133 × 1011
Variance4.1486347 × 1015
MonotonicityNot monotonic
2024-07-05T20:16:50.678961image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37949
83.7%
12000000 20
 
< 0.1%
10000000 19
 
< 0.1%
11000000 19
 
< 0.1%
2000000 18
 
< 0.1%
6000000 17
 
< 0.1%
5000000 14
 
< 0.1%
500000 13
 
< 0.1%
8000000 13
 
< 0.1%
14000000 12
 
< 0.1%
Other values (6853) 7252
 
16.0%
ValueCountFrequency (%)
0 37949
83.7%
1 12
 
< 0.1%
2 3
 
< 0.1%
3 9
 
< 0.1%
4 4
 
< 0.1%
5 5
 
< 0.1%
6 2
 
< 0.1%
7 4
 
< 0.1%
8 5
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
2787965087 1
< 0.1%
2068223624 1
< 0.1%
1845034188 1
< 0.1%
1519557910 1
< 0.1%
1513528810 1
< 0.1%
1506249360 1
< 0.1%
1405403694 1
< 0.1%
1342000000 1
< 0.1%
1274219009 1
< 0.1%
1262886337 1
< 0.1%
Distinct44232
Distinct (%)97.6%
Missing5
Missing (%)< 0.1%
Memory size354.4 KiB
2024-07-05T20:16:50.840378image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length1000
Median length790
Mean length316.73256
Min length1

Characters and Unicode

Total characters14360971
Distinct characters429
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44201 ?
Unique (%)97.5%

Sample

1st rowA card sharp and his unwillingly-enlisted friends need to make a lot of cash quick after losing a sketchy poker match. To do this they decide to pull a heist on a small-time gang who happen to be operating out of the flat next door.
2nd rowA group of tenants living in an old house are confronted with having to move out due to a renovation project the city has undertaken. The tenants decide to unite and come up with a strategy, but in the process—while the landlord and his aggressive attorney are chasing them—the tenants transform into the opposite of who they once were.
3rd rowAlbert Einstein is the son of a Tasmanian apple farmer, who discovers the secret of splitting the beer atom to put the bubbles back into beer. When Albert travels to Sydney to patent his invention he meets beatuiful French scientist Marie Curie, as well as several unscrupulous types who try to take advantage of the naive genius and his invention.
4th rowA rookie flyer, Ens. Alan Drake, joins the famous Hellcats Squadron right out of flight school in Pensacola. He doesn't make a great first impression when he is forced to ditch his airplane and parachute to safety when he arrives at the base but is unable to land due to heavy fog. On his first day on the job, his poor shooting skills results in the Hellcats losing an air combat competition. His fellow pilots accept him anyways but they think he's crossed the line when they erroneously conclude that while their CO Billy Gray is away, Drake has an affair with his wife Lorna. Drake is now an outcast and is prepared to resign from the Navy but his extreme heroism in saving Billy Gray's life turns things around.
5th rowDeals with the obsessive relationship between a confused teenager and an elder woman. Elsa Seifert successfully works as probation officer, but the relationship to her longtime companion is in trouble since their common daughter moved out. Then she gets to know Jan, a 16-years-old offender, who frankly offers to submit himself sexually to her. Although being shocked in the beginning, Elsa gets more and more attracted by the young man
ValueCountFrequency (%)
the 137966
 
5.6%
a 98825
 
4.0%
and 75193
 
3.1%
to 73261
 
3.0%
of 69523
 
2.8%
in 48107
 
2.0%
is 36479
 
1.5%
his 36130
 
1.5%
with 23880
 
1.0%
her 21460
 
0.9%
Other values (97092) 1826899
74.6%
2024-07-05T20:16:51.080282image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2404448
16.7%
e 1362739
 
9.5%
a 940662
 
6.6%
t 934997
 
6.5%
i 851783
 
5.9%
o 830192
 
5.8%
n 822891
 
5.7%
s 767224
 
5.3%
r 743645
 
5.2%
h 600339
 
4.2%
Other values (419) 4102051
28.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14360971
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2404448
16.7%
e 1362739
 
9.5%
a 940662
 
6.6%
t 934997
 
6.5%
i 851783
 
5.9%
o 830192
 
5.8%
n 822891
 
5.7%
s 767224
 
5.3%
r 743645
 
5.2%
h 600339
 
4.2%
Other values (419) 4102051
28.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14360971
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2404448
16.7%
e 1362739
 
9.5%
a 940662
 
6.6%
t 934997
 
6.5%
i 851783
 
5.9%
o 830192
 
5.8%
n 822891
 
5.7%
s 767224
 
5.3%
r 743645
 
5.2%
h 600339
 
4.2%
Other values (419) 4102051
28.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14360971
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2404448
16.7%
e 1362739
 
9.5%
a 940662
 
6.6%
t 934997
 
6.5%
i 851783
 
5.9%
o 830192
 
5.8%
n 822891
 
5.7%
s 767224
 
5.3%
r 743645
 
5.2%
h 600339
 
4.2%
Other values (419) 4102051
28.6%
Distinct17333
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Memory size354.4 KiB
Minimum1874-12-09 00:00:00
Maximum2020-12-16 00:00:00
2024-07-05T20:16:51.154722image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:51.206332image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

vote_average
Real number (ℝ)

ZEROS 

Distinct92
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6241962
Minimum0
Maximum10
Zeros2944
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:51.257608image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median6
Q36.8
95-th percentile7.8
Maximum10
Range10
Interquartile range (IQR)1.8

Descriptive statistics

Standard deviation1.915339
Coefficient of variation (CV)0.34055337
Kurtosis2.5420383
Mean5.6241962
Median Absolute Deviation (MAD)0.9
Skewness-1.5243174
Sum255034.8
Variance3.6685234
MonotonicityNot monotonic
2024-07-05T20:16:51.307955image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2944
 
6.5%
6 2461
 
5.4%
5 1994
 
4.4%
7 1882
 
4.2%
6.5 1722
 
3.8%
6.3 1602
 
3.5%
5.5 1381
 
3.0%
5.8 1369
 
3.0%
6.4 1348
 
3.0%
6.7 1339
 
3.0%
Other values (82) 27304
60.2%
ValueCountFrequency (%)
0 2944
6.5%
0.5 13
 
< 0.1%
0.7 1
 
< 0.1%
1 103
 
0.2%
1.1 1
 
< 0.1%
1.2 4
 
< 0.1%
1.3 13
 
< 0.1%
1.4 5
 
< 0.1%
1.5 30
 
0.1%
1.6 6
 
< 0.1%
ValueCountFrequency (%)
10 185
0.4%
9.8 1
 
< 0.1%
9.6 1
 
< 0.1%
9.5 18
 
< 0.1%
9.4 3
 
< 0.1%
9.3 18
 
< 0.1%
9.2 4
 
< 0.1%
9.1 2
 
< 0.1%
9 158
0.3%
8.9 7
 
< 0.1%

vote_count
Real number (ℝ)

ZEROS 

Distinct1820
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110.13529
Minimum0
Maximum14075
Zeros2846
Zeros (%)6.3%
Negative0
Negative (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:51.354775image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median10
Q334
95-th percentile434.75
Maximum14075
Range14075
Interquartile range (IQR)31

Descriptive statistics

Standard deviation491.89928
Coefficient of variation (CV)4.4663183
Kurtosis150.83135
Mean110.13529
Median Absolute Deviation (MAD)8
Skewness10.437494
Sum4994195
Variance241964.9
MonotonicityNot monotonic
2024-07-05T20:16:51.403740image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3240
 
7.1%
2 3127
 
6.9%
0 2846
 
6.3%
3 2780
 
6.1%
4 2477
 
5.5%
5 2096
 
4.6%
6 1747
 
3.9%
7 1568
 
3.5%
8 1359
 
3.0%
9 1194
 
2.6%
Other values (1810) 22912
50.5%
ValueCountFrequency (%)
0 2846
6.3%
1 3240
7.1%
2 3127
6.9%
3 2780
6.1%
4 2477
5.5%
5 2096
4.6%
6 1747
3.9%
7 1568
3.5%
8 1359
3.0%
9 1194
 
2.6%
ValueCountFrequency (%)
14075 1
< 0.1%
12269 1
< 0.1%
12114 1
< 0.1%
12000 1
< 0.1%
11444 1
< 0.1%
11187 1
< 0.1%
10297 1
< 0.1%
10014 1
< 0.1%
9678 1
< 0.1%
9634 1
< 0.1%

popularity
Real number (ℝ)

SKEWED 

Distinct43719
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.926188
Minimum0
Maximum547.4883
Zeros40
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:51.452925image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.020823
Q10.38873225
median1.130176
Q33.6893365
95-th percentile11.063757
Maximum547.4883
Range547.4883
Interquartile range (IQR)3.3006043

Descriptive statistics

Standard deviation6.0109699
Coefficient of variation (CV)2.0541981
Kurtosis1923.3033
Mean2.926188
Median Absolute Deviation (MAD)0.967289
Skewness29.215423
Sum132690.92
Variance36.131759
MonotonicityNot monotonic
2024-07-05T20:16:51.500369image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 × 10-656
 
0.1%
0.000308 42
 
0.1%
0 40
 
0.1%
0.00022 39
 
0.1%
0.000578 38
 
0.1%
0.000844 38
 
0.1%
0.001177 38
 
0.1%
0.002001 27
 
0.1%
0.003013 21
 
< 0.1%
0.00353 19
 
< 0.1%
Other values (43709) 44988
99.2%
ValueCountFrequency (%)
0 40
0.1%
1 × 10-656
0.1%
2 × 10-66
 
< 0.1%
3 × 10-66
 
< 0.1%
4 × 10-65
 
< 0.1%
5 × 10-61
 
< 0.1%
6 × 10-62
 
< 0.1%
7 × 10-61
 
< 0.1%
8 × 10-66
 
< 0.1%
9 × 10-62
 
< 0.1%
ValueCountFrequency (%)
547.488298 1
< 0.1%
294.337037 1
< 0.1%
287.253654 1
< 0.1%
228.032744 1
< 0.1%
213.849907 1
< 0.1%
187.860492 1
< 0.1%
185.330992 1
< 0.1%
185.070892 1
< 0.1%
183.870374 1
< 0.1%
154.801009 1
< 0.1%

runtime
Real number (ℝ)

ZEROS 

Distinct353
Distinct (%)0.8%
Missing246
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean94.177805
Minimum0
Maximum1256
Zeros1535
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:51.549442image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q185
median95
Q3107
95-th percentile138
Maximum1256
Range1256
Interquartile range (IQR)22

Descriptive statistics

Standard deviation38.348775
Coefficient of variation (CV)0.40719547
Kurtosis93.913375
Mean94.177805
Median Absolute Deviation (MAD)11
Skewness4.4911098
Sum4247419
Variance1470.6286
MonotonicityNot monotonic
2024-07-05T20:16:51.601017image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 2548
 
5.6%
0 1535
 
3.4%
100 1470
 
3.2%
95 1409
 
3.1%
93 1212
 
2.7%
96 1104
 
2.4%
92 1078
 
2.4%
94 1061
 
2.3%
91 1055
 
2.3%
88 1030
 
2.3%
Other values (343) 31598
69.7%
ValueCountFrequency (%)
0 1535
3.4%
1 107
 
0.2%
2 33
 
0.1%
3 48
 
0.1%
4 50
 
0.1%
5 51
 
0.1%
6 72
 
0.2%
7 103
 
0.2%
8 78
 
0.2%
9 63
 
0.1%
ValueCountFrequency (%)
1256 1
< 0.1%
1140 2
< 0.1%
931 1
< 0.1%
925 1
< 0.1%
900 1
< 0.1%
877 1
< 0.1%
874 1
< 0.1%
840 2
< 0.1%
780 1
< 0.1%
720 1
< 0.1%

status
Categorical

IMBALANCE 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size354.4 KiB
Released
44907 
Rumored
 
229
Post Production
 
97
SinDato
 
80
In Production
 
19
Other values (2)
 
14

Length

Max length15
Median length8
Mean length8.0099678
Min length7

Characters and Unicode

Total characters363220
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowReleased
2nd rowReleased
3rd rowReleased
4th rowReleased
5th rowReleased

Common Values

ValueCountFrequency (%)
Released 44907
99.0%
Rumored 229
 
0.5%
Post Production 97
 
0.2%
SinDato 80
 
0.2%
In Production 19
 
< 0.1%
Planned 13
 
< 0.1%
Canceled 1
 
< 0.1%

Length

2024-07-05T20:16:51.650684image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-05T20:16:51.696046image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
released 44907
98.8%
rumored 229
 
0.5%
production 116
 
0.3%
post 97
 
0.2%
sindato 80
 
0.2%
in 19
 
< 0.1%
planned 13
 
< 0.1%
canceled 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 134965
37.2%
d 45266
 
12.5%
R 45136
 
12.4%
s 45004
 
12.4%
a 45001
 
12.4%
l 44921
 
12.4%
o 638
 
0.2%
u 345
 
0.1%
r 345
 
0.1%
t 293
 
0.1%
Other values (10) 1306
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 363220
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 134965
37.2%
d 45266
 
12.5%
R 45136
 
12.4%
s 45004
 
12.4%
a 45001
 
12.4%
l 44921
 
12.4%
o 638
 
0.2%
u 345
 
0.1%
r 345
 
0.1%
t 293
 
0.1%
Other values (10) 1306
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 363220
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 134965
37.2%
d 45266
 
12.5%
R 45136
 
12.4%
s 45004
 
12.4%
a 45001
 
12.4%
l 44921
 
12.4%
o 638
 
0.2%
u 345
 
0.1%
r 345
 
0.1%
t 293
 
0.1%
Other values (10) 1306
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 363220
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 134965
37.2%
d 45266
 
12.5%
R 45136
 
12.4%
s 45004
 
12.4%
a 45001
 
12.4%
l 44921
 
12.4%
o 638
 
0.2%
u 345
 
0.1%
r 345
 
0.1%
t 293
 
0.1%
Other values (10) 1306
 
0.4%
Distinct20269
Distinct (%)44.7%
Missing1
Missing (%)< 0.1%
Memory size354.4 KiB
2024-07-05T20:16:51.859339image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length297
Median length7
Mean length24.982424
Min length1

Characters and Unicode

Total characters1132828
Distinct characters170
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20172 ?
Unique (%)44.5%

Sample

1st rowA Disgrace to Criminals Everywhere.
2nd rowSinDato
3rd rowE=mc²
4th rowT-H-R-I-L-L AMERICA! Here come The Flying "HELL CATS"!
5th rowSinDato
ValueCountFrequency (%)
sindato 24959
 
12.6%
the 10987
 
5.5%
a 6810
 
3.4%
of 4401
 
2.2%
to 3581
 
1.8%
is 2793
 
1.4%
in 2691
 
1.4%
and 2681
 
1.3%
you 2388
 
1.2%
1580
 
0.8%
Other values (15101) 135917
68.4%
2024-07-05T20:16:52.106763image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
153587
13.6%
e 94342
 
8.3%
t 82182
 
7.3%
o 81493
 
7.2%
a 76409
 
6.7%
n 72419
 
6.4%
i 70972
 
6.3%
r 44957
 
4.0%
s 42345
 
3.7%
h 37144
 
3.3%
Other values (160) 376978
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1132828
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
153587
13.6%
e 94342
 
8.3%
t 82182
 
7.3%
o 81493
 
7.2%
a 76409
 
6.7%
n 72419
 
6.4%
i 70972
 
6.3%
r 44957
 
4.0%
s 42345
 
3.7%
h 37144
 
3.3%
Other values (160) 376978
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1132828
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
153587
13.6%
e 94342
 
8.3%
t 82182
 
7.3%
o 81493
 
7.2%
a 76409
 
6.7%
n 72419
 
6.4%
i 70972
 
6.3%
r 44957
 
4.0%
s 42345
 
3.7%
h 37144
 
3.3%
Other values (160) 376978
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1132828
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
153587
13.6%
e 94342
 
8.3%
t 82182
 
7.3%
o 81493
 
7.2%
a 76409
 
6.7%
n 72419
 
6.4%
i 70972
 
6.3%
r 44957
 
4.0%
s 42345
 
3.7%
h 37144
 
3.3%
Other values (160) 376978
33.3%
Distinct10611
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:52.274419image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length91
Median length66
Mean length15.673643
Min length2

Characters and Unicode

Total characters710737
Distinct characters252
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7069 ?
Unique (%)15.6%

Sample

1st rowHandmade Films Ltd.
2nd rowMinistère de la Culture et de la Francophonie
3rd rowWarner Bros.
4th rowMetro-Goldwyn-Mayer (MGM)
5th rowMMM Film Zimmermann & Co
ValueCountFrequency (%)
sindato 11789
 
12.4%
pictures 6295
 
6.6%
films 4187
 
4.4%
productions 3773
 
4.0%
film 3556
 
3.7%
entertainment 2104
 
2.2%
corporation 1686
 
1.8%
fox 1039
 
1.1%
paramount 1035
 
1.1%
universal 964
 
1.0%
Other values (9739) 58958
61.8%
2024-07-05T20:16:52.496947image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 63054
 
8.9%
o 53312
 
7.5%
n 53042
 
7.5%
t 52562
 
7.4%
50044
 
7.0%
a 48304
 
6.8%
e 44162
 
6.2%
r 42079
 
5.9%
s 30682
 
4.3%
l 24074
 
3.4%
Other values (242) 249422
35.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 710737
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 63054
 
8.9%
o 53312
 
7.5%
n 53042
 
7.5%
t 52562
 
7.4%
50044
 
7.0%
a 48304
 
6.8%
e 44162
 
6.2%
r 42079
 
5.9%
s 30682
 
4.3%
l 24074
 
3.4%
Other values (242) 249422
35.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 710737
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 63054
 
8.9%
o 53312
 
7.5%
n 53042
 
7.5%
t 52562
 
7.4%
50044
 
7.0%
a 48304
 
6.8%
e 44162
 
6.2%
r 42079
 
5.9%
s 30682
 
4.3%
l 24074
 
3.4%
Other values (242) 249422
35.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 710737
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 63054
 
8.9%
o 53312
 
7.5%
n 53042
 
7.5%
t 52562
 
7.4%
50044
 
7.0%
a 48304
 
6.8%
e 44162
 
6.2%
r 42079
 
5.9%
s 30682
 
4.3%
l 24074
 
3.4%
Other values (242) 249422
35.1%
Distinct144
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:52.645707image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length36
Median length32
Mean length14.213911
Min length4

Characters and Unicode

Total characters644544
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)< 0.1%

Sample

1st rowUnited Kingdom
2nd rowColombia
3rd rowAustralia
4th rowUnited States of America
5th rowGermany
ValueCountFrequency (%)
united 21490
20.5%
states 18411
17.5%
of 18410
17.5%
america 18410
17.5%
sindato 6208
 
5.9%
kingdom 3066
 
2.9%
france 2699
 
2.6%
canada 1498
 
1.4%
japan 1490
 
1.4%
italy 1470
 
1.4%
Other values (161) 11893
11.3%
2024-07-05T20:16:52.844323image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 68042
 
10.6%
e 67165
 
10.4%
a 64345
 
10.0%
59699
 
9.3%
i 55183
 
8.6%
n 44111
 
6.8%
o 30836
 
4.8%
d 28572
 
4.4%
S 26374
 
4.1%
r 26146
 
4.1%
Other values (42) 174071
27.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 644544
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 68042
 
10.6%
e 67165
 
10.4%
a 64345
 
10.0%
59699
 
9.3%
i 55183
 
8.6%
n 44111
 
6.8%
o 30836
 
4.8%
d 28572
 
4.4%
S 26374
 
4.1%
r 26146
 
4.1%
Other values (42) 174071
27.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 644544
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 68042
 
10.6%
e 67165
 
10.4%
a 64345
 
10.0%
59699
 
9.3%
i 55183
 
8.6%
n 44111
 
6.8%
o 30836
 
4.8%
d 28572
 
4.4%
S 26374
 
4.1%
r 26146
 
4.1%
Other values (42) 174071
27.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 644544
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 68042
 
10.6%
e 67165
 
10.4%
a 64345
 
10.0%
59699
 
9.3%
i 55183
 
8.6%
n 44111
 
6.8%
o 30836
 
4.8%
d 28572
 
4.4%
S 26374
 
4.1%
r 26146
 
4.1%
Other values (42) 174071
27.0%

release_year
Real number (ℝ)

Distinct135
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1991.8828
Minimum1874
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:52.915350image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1874
5-th percentile1941
Q11978
median2001
Q32010
95-th percentile2015
Maximum2020
Range146
Interquartile range (IQR)32

Descriptive statistics

Standard deviation24.05304
Coefficient of variation (CV)0.01207553
Kurtosis0.84037057
Mean1991.8828
Median Absolute Deviation (MAD)12
Skewness-1.2247867
Sum90323919
Variance578.54874
MonotonicityNot monotonic
2024-07-05T20:16:53.069091image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2014 1973
 
4.4%
2015 1904
 
4.2%
2013 1887
 
4.2%
2012 1721
 
3.8%
2011 1666
 
3.7%
2016 1604
 
3.5%
2009 1585
 
3.5%
2010 1501
 
3.3%
2008 1470
 
3.2%
2007 1319
 
2.9%
Other values (125) 28716
63.3%
ValueCountFrequency (%)
1874 1
 
< 0.1%
1878 1
 
< 0.1%
1883 1
 
< 0.1%
1887 1
 
< 0.1%
1888 2
 
< 0.1%
1890 5
 
< 0.1%
1891 6
< 0.1%
1892 3
 
< 0.1%
1893 1
 
< 0.1%
1894 13
< 0.1%
ValueCountFrequency (%)
2020 1
 
< 0.1%
2018 5
 
< 0.1%
2017 532
 
1.2%
2016 1604
3.5%
2015 1904
4.2%
2014 1973
4.4%
2013 1887
4.2%
2012 1721
3.8%
2011 1666
3.7%
2010 1501
3.3%

return
Real number (ℝ)

SKEWED  ZEROS 

Distinct5232
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean660.47916
Minimum0
Maximum12396383
Zeros39971
Zeros (%)88.1%
Negative0
Negative (%)0.0%
Memory size354.4 KiB
2024-07-05T20:16:53.121676image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.5347418
Maximum12396383
Range12396383
Interquartile range (IQR)0

Descriptive statistics

Standard deviation74717.996
Coefficient of variation (CV)113.12695
Kurtosis20659.288
Mean660.47916
Median Absolute Deviation (MAD)0
Skewness138.28379
Sum29950088
Variance5.582779 × 109
MonotonicityNot monotonic
2024-07-05T20:16:53.175834image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39971
88.1%
1 20
 
< 0.1%
2 12
 
< 0.1%
4 11
 
< 0.1%
5 8
 
< 0.1%
3 7
 
< 0.1%
1.333333333 7
 
< 0.1%
2.5 7
 
< 0.1%
1.5 6
 
< 0.1%
4.666666667 4
 
< 0.1%
Other values (5222) 5293
 
11.7%
ValueCountFrequency (%)
0 39971
88.1%
5.217391304 × 10-71
 
< 0.1%
7.5 × 10-71
 
< 0.1%
9.375 × 10-71
 
< 0.1%
1.499133126 × 10-61
 
< 0.1%
1.8 × 10-61
 
< 0.1%
1.916666667 × 10-61
 
< 0.1%
3.5 × 10-61
 
< 0.1%
4 × 10-61
 
< 0.1%
5.111111111 × 10-61
 
< 0.1%
ValueCountFrequency (%)
12396383 1
< 0.1%
8500000 1
< 0.1%
4197476.625 1
< 0.1%
2755584 1
< 0.1%
1018619.283 1
< 0.1%
1000000 1
< 0.1%
26881.72043 1
< 0.1%
12890.38667 1
< 0.1%
5330.33945 1
< 0.1%
4133.333333 1
< 0.1%

director
Text

MISSING 

Distinct17548
Distinct (%)39.4%
Missing836
Missing (%)1.8%
Memory size354.4 KiB
2024-07-05T20:16:53.330101image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length33
Median length29
Mean length13.465603
Min length2

Characters and Unicode

Total characters599354
Distinct characters200
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10606 ?
Unique (%)23.8%

Sample

1st rowGuy Ritchie
2nd rowSergio Cabrera
3rd rowYahoo Serious
4th rowFrank Borzage
5th rowAngelina Maccarone
ValueCountFrequency (%)
john 1163
 
1.2%
michael 877
 
0.9%
david 806
 
0.9%
robert 805
 
0.9%
peter 524
 
0.6%
william 513
 
0.5%
richard 511
 
0.5%
james 489
 
0.5%
paul 436
 
0.5%
george 396
 
0.4%
Other values (17074) 87051
93.0%
2024-07-05T20:16:53.561782image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 52237
 
8.7%
a 51616
 
8.6%
49163
 
8.2%
r 40733
 
6.8%
n 40183
 
6.7%
i 38944
 
6.5%
o 35305
 
5.9%
l 27432
 
4.6%
s 20755
 
3.5%
t 19727
 
3.3%
Other values (190) 223259
37.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 599354
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 52237
 
8.7%
a 51616
 
8.6%
49163
 
8.2%
r 40733
 
6.8%
n 40183
 
6.7%
i 38944
 
6.5%
o 35305
 
5.9%
l 27432
 
4.6%
s 20755
 
3.5%
t 19727
 
3.3%
Other values (190) 223259
37.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 599354
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 52237
 
8.7%
a 51616
 
8.6%
49163
 
8.2%
r 40733
 
6.8%
n 40183
 
6.7%
i 38944
 
6.5%
o 35305
 
5.9%
l 27432
 
4.6%
s 20755
 
3.5%
t 19727
 
3.3%
Other values (190) 223259
37.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 599354
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 52237
 
8.7%
a 51616
 
8.6%
49163
 
8.2%
r 40733
 
6.8%
n 40183
 
6.7%
i 38944
 
6.5%
o 35305
 
5.9%
l 27432
 
4.6%
s 20755
 
3.5%
t 19727
 
3.3%
Other values (190) 223259
37.2%

actor
Text

MISSING 

Distinct42291
Distinct (%)98.6%
Missing2474
Missing (%)5.5%
Memory size354.4 KiB
2024-07-05T20:16:53.755759image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length19534
Median length1703
Mean length217.04049
Min length4

Characters and Unicode

Total characters9304960
Distinct characters395
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42152 ?
Unique (%)98.3%

Sample

1st rowJason Flemyng, Dexter Fletcher, Nick Moran, Jason Statham, Vinnie Jones, Sting, Steven Mackintosh, Nicholas Rowe, Lenny McLean, P.H. Moriarty, Frank Harper, Huggy Leaver, Stephen Marcus, Peter McNicholl, Nick Marcq, Tony McMahon, Steve Sweeney, Charles Forbes, Vas Blackwood, Jake Abraham, Victor McGuire, Danny John-Jules, Elwin 'Chopper' David, Vera Day, Rob Brydon, Alan Ford, Andrew Tiernan
2nd rowYahoo Serious, Odile Le Clezio, Peewee Wilson, Su Cruickshank, John Howard, Christian Manon
3rd rowRobert Taylor, Ruth Hussey, Walter Pidgeon, Paul Kelly, Shepperd Strudwick, Red Skelton, Nat Pendleton, Dick Purcell, William Tannen, William Stelling, Stanley Smith, Addison Richards, Donald Douglas, Pat Flaherty, Forbes Murray, Marsha Hunt, Cliff Danielson, Bob Davis, Lee Tung Foo, Reed Hadley, John Hamilton, Otto Han, Hal Le Sueur, Jack Luden, James Millican, Alberto Morin, Tom Neal, George Offerman Jr., Claire Owen, Steve Pendleton, John Raitt, Walter Sande, James Seay, John Sheehan, Dick Wessel, Gayne Whitman, Gilbert Wilson, Howard Wilson, Bruce Edwards
4th rowKostja Ullmann, Maren Kroymann, Moritz Grove, Sıla Şahin, Ada Labahn, Markus Voellenklee, Stephanie Charlotta Koetz, Sophie Rogall, Michael Pink, Frank Meyer-Brockmann
5th rowBob Hoskins, Cathy Tyson, Michael Caine, Robbie Coltrane, Clarke Peters, Kate Hardie, Zoë Nathenson, Sammi Davis, Joe Brown, Pauline Melville, Hossein Karimbeik, David Halliwell, Maggie O'Neill, Perry Fenwick, Gary Cady, Richard Strange, Kenny Baker, Jack Purvis, Bill Moore, Rod Bedall, Raad Rawi, Dawn Archibald
ValueCountFrequency (%)
john 10596
 
0.8%
michael 8097
 
0.6%
david 6697
 
0.5%
james 6214
 
0.5%
robert 6092
 
0.5%
richard 4785
 
0.4%
paul 4702
 
0.4%
peter 4231
 
0.3%
william 3696
 
0.3%
george 3690
 
0.3%
Other values (112661) 1212775
95.4%
2024-07-05T20:16:54.018017image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1228840
 
13.2%
a 769994
 
8.3%
e 725331
 
7.8%
n 573287
 
6.2%
, 571449
 
6.1%
r 541991
 
5.8%
i 528844
 
5.7%
o 462118
 
5.0%
l 399442
 
4.3%
s 279647
 
3.0%
Other values (385) 3224017
34.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9304960
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1228840
 
13.2%
a 769994
 
8.3%
e 725331
 
7.8%
n 573287
 
6.2%
, 571449
 
6.1%
r 541991
 
5.8%
i 528844
 
5.7%
o 462118
 
5.0%
l 399442
 
4.3%
s 279647
 
3.0%
Other values (385) 3224017
34.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9304960
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1228840
 
13.2%
a 769994
 
8.3%
e 725331
 
7.8%
n 573287
 
6.2%
, 571449
 
6.1%
r 541991
 
5.8%
i 528844
 
5.7%
o 462118
 
5.0%
l 399442
 
4.3%
s 279647
 
3.0%
Other values (385) 3224017
34.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9304960
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1228840
 
13.2%
a 769994
 
8.3%
e 725331
 
7.8%
n 573287
 
6.2%
, 571449
 
6.1%
r 541991
 
5.8%
i 528844
 
5.7%
o 462118
 
5.0%
l 399442
 
4.3%
s 279647
 
3.0%
Other values (385) 3224017
34.6%

Interactions

2024-07-05T20:16:48.581832image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:45.486037image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:45.986981image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.340633image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.735704image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.074374image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.427135image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.810409image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.224540image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.618311image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:45.563590image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.024138image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.376569image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.771031image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.112022image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.461230image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.847081image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.261734image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.658008image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:45.689998image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.064050image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.415900image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.810913image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.152508image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.501864image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.886919image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.302965image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.696043image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:45.764305image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.102120image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.451728image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.848909image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.191305image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.539787image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.991870image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.341752image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.733558image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:45.801629image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.140246image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.489151image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.883780image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.228360image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.576929image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.030456image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.380437image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.773148image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:45.839928image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.181572image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.527316image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.922909image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.269446image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.620579image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.070890image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.421456image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.808621image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:45.876229image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.219095image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.564875image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.959249image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.306152image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.693135image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.106949image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.461350image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.846239image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:45.911566image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.259044image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.602298image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.997680image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.345870image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.730225image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.144885image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.501513image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.887103image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:45.950141image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.300640image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:46.641595image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.037169image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.388075image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:47.770529image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.185594image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-05T20:16:48.542475image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Missing values

2024-07-05T20:16:48.955468image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-05T20:16:49.091460image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-07-05T20:16:49.262293image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idspoken_languagesnamegenresnametitlebudgetrevenueoverviewrelease_datevote_averagevote_countpopularityruntimestatustaglineproduction_companiesnameproduction_countriesnamerelease_yearreturndirectoractor
0100EnglishComedy, CrimeLock, Stock and Two Smoking Barrels1350000.03897569.0A card sharp and his unwillingly-enlisted friends need to make a lot of cash quick after losing a sketchy poker match. To do this they decide to pull a heist on a small-time gang who happen to be operating out of the flat next door.1998-03-057.51671.04.607860105.0ReleasedA Disgrace to Criminals Everywhere.Handmade Films Ltd.United Kingdom1998.02.887088Guy RitchieJason Flemyng, Dexter Fletcher, Nick Moran, Jason Statham, Vinnie Jones, Sting, Steven Mackintosh, Nicholas Rowe, Lenny McLean, P.H. Moriarty, Frank Harper, Huggy Leaver, Stephen Marcus, Peter McNicholl, Nick Marcq, Tony McMahon, Steve Sweeney, Charles Forbes, Vas Blackwood, Jake Abraham, Victor McGuire, Danny John-Jules, Elwin 'Chopper' David, Vera Day, Rob Brydon, Alan Ford, Andrew Tiernan
110000EspañolComedy, DramaLa estrategia del caracol0.00.0A group of tenants living in an old house are confronted with having to move out due to a renovation project the city has undertaken. The tenants decide to unite and come up with a strategy, but in the process—while the landlord and his aggressive attorney are chasing them—the tenants transform into the opposite of who they once were.1993-12-257.29.00.281609116.0ReleasedSinDatoMinistère de la Culture et de la FrancophonieColombia1993.00.000000Sergio CabreraNaN
210001EnglishComedy, Science FictionYoung Einstein0.00.0Albert Einstein is the son of a Tasmanian apple farmer, who discovers the secret of splitting the beer atom to put the bubbles back into beer. When Albert travels to Sydney to patent his invention he meets beatuiful French scientist Marie Curie, as well as several unscrupulous types who try to take advantage of the naive genius and his invention.1988-12-154.546.02.56288891.0ReleasedE=mc²Warner Bros.Australia1988.00.000000Yahoo SeriousYahoo Serious, Odile Le Clezio, Peewee Wilson, Su Cruickshank, John Howard, Christian Manon
3100010EnglishWar, DramaFlight Command0.00.0A rookie flyer, Ens. Alan Drake, joins the famous Hellcats Squadron right out of flight school in Pensacola. He doesn't make a great first impression when he is forced to ditch his airplane and parachute to safety when he arrives at the base but is unable to land due to heavy fog. On his first day on the job, his poor shooting skills results in the Hellcats losing an air combat competition. His fellow pilots accept him anyways but they think he's crossed the line when they erroneously conclude that while their CO Billy Gray is away, Drake has an affair with his wife Lorna. Drake is now an outcast and is prepared to resign from the Navy but his extreme heroism in saving Billy Gray's life turns things around.1940-12-276.01.00.769266116.0ReleasedT-H-R-I-L-L AMERICA! Here come The Flying "HELL CATS"!Metro-Goldwyn-Mayer (MGM)United States of America1940.00.000000Frank BorzageRobert Taylor, Ruth Hussey, Walter Pidgeon, Paul Kelly, Shepperd Strudwick, Red Skelton, Nat Pendleton, Dick Purcell, William Tannen, William Stelling, Stanley Smith, Addison Richards, Donald Douglas, Pat Flaherty, Forbes Murray, Marsha Hunt, Cliff Danielson, Bob Davis, Lee Tung Foo, Reed Hadley, John Hamilton, Otto Han, Hal Le Sueur, Jack Luden, James Millican, Alberto Morin, Tom Neal, George Offerman Jr., Claire Owen, Steve Pendleton, John Raitt, Walter Sande, James Seay, John Sheehan, Dick Wessel, Gayne Whitman, Gilbert Wilson, Howard Wilson, Bruce Edwards
4100017DeutschDramaHounded0.00.0Deals with the obsessive relationship between a confused teenager and an elder woman. Elsa Seifert successfully works as probation officer, but the relationship to her longtime companion is in trouble since their common daughter moved out. Then she gets to know Jan, a 16-years-old offender, who frankly offers to submit himself sexually to her. Although being shocked in the beginning, Elsa gets more and more attracted by the young man2006-08-064.87.02.96410387.0ReleasedSinDatoMMM Film Zimmermann & CoGermany2006.00.000000Angelina MaccaroneKostja Ullmann, Maren Kroymann, Moritz Grove, Sıla Şahin, Ada Labahn, Markus Voellenklee, Stephanie Charlotta Koetz, Sophie Rogall, Michael Pink, Frank Meyer-Brockmann
510002EnglishRomance, Crime, DramaMona Lisa0.05794184.0George has just been released from prison, and manages to get a job driving an expensive call girl from customer to customer. Initially they don't get on - he doesn't fit in with the high class customers Simone services. Will they ever get on?1986-06-136.762.03.095584104.0ReleasedSinDatoThe Criterion CollectionUnited Kingdom1986.00.000000Neil JordanBob Hoskins, Cathy Tyson, Michael Caine, Robbie Coltrane, Clarke Peters, Kate Hardie, Zoë Nathenson, Sammi Davis, Joe Brown, Pauline Melville, Hossein Karimbeik, David Halliwell, Maggie O'Neill, Perry Fenwick, Gary Cady, Richard Strange, Kenny Baker, Jack Purvis, Bill Moore, Rod Bedall, Raad Rawi, Dawn Archibald
6100024EnglishHorror, ThrillerBloodwork0.00.0A couple of college students decide to sign up for pharmaceutical testing of a new allergy drug to make some extra cash for their spring break trip. They quickly discover their two week stay will not be as easy as they first believed and fight to save themselves from the grips of the facility.2012-05-104.313.01.099911100.0ReleasedNot Dying Doesn't Mean You're AliveSinDatoUnited States of America2012.00.000000Eric WostenbergTravis Van Winkle, Tricia Helfer, Eric Roberts, John Bregar
710003Pусский, EnglishRomance, Thriller, Adventure, Science Fiction, ActionThe Saint68000000.0118063304.0Ivan Tretiak, Russian Mafia boss who wants to create an oil crisis in Moscow and seize power as a result sends Simon Templar, great international criminal, to England to get a secret formula for cold fusion from U.S. scientist Emma Russell. Templar falls in love with Emma and they try to outwit Tretiak and his guerrillas, hiding from them in Moscow1997-04-035.9310.010.976330116.0ReleasedNever reveal your name. Never turn your back. Never surrender your heart.Paramount PicturesUnited States of America1997.01.736225Phillip NoyceVal Kilmer, Elisabeth Shue, Rade Serbedzija, Henry Goodman, Alun Armstrong, Michael Byrne, Yevgeni Lazarev, Irina Apeksimova, Lev Prygunov, Charlotte Cornwell, Emily Mortimer, Lucija Serbedzija, Velibor Topic, Tommy Flanagan, Egor Pazenko, Adam Smith, Pat Laffan, Verity-Jane Dearsley, Michael Marquez, Lorelei King, Alla Kazanskaya, Ronnie Letham, Tusse Silberg, Peter Guinness, Stefan Gryff, Malcolm Tierney, Christopher Rozycki, Valeriy Nikolaev
8100032EnglishAction, DramaThe Great Los Angeles Earthquake0.00.0After a series of small tremors in Los Angeles, Dr. Clare Winslow, a local seismologist, pinpoints the exact location and time of when the long awaited earthquake--"The Big One"--will strike southern California. With this information, she must battle city officials to release this information to the general public. Also, she hopes that her family is out of harms way when the quake strikes. Subplots show how other families and people cope with the the tremors that strike before the impending "Big One."1990-11-116.85.01.315925180.0ReleasedThere is no safe harbor, there is no escape... L.A.'s worst fear has just become a reality.Von Zerneck Sertner FilmsUnited States of America1990.00.000000Larry ElikannJoanna Kerns, Dan Lauria, Bonnie Bartlett, Lindsay Frost, Alan Autry, Joe Spano, Holly Fields, Brock Peters, Stephen Elliott, Robert Ginty, Clarence Gilyard Jr., Silvana Gallardo, Michael T. Weiss, Charles Siebert, Richard Herd, J. Kenneth Campbell, Richard Masur, Ed Begley Jr., Richard Anthony Crenna, Kasi Lemmons, Allan Wasserman, Ross Kettle, Eloy Casados, Jacob Vargas, Mort Sertner
9100033日本語DramaMr. Thank You0.00.0Japanese film about a friendly bus driver and his passengers over the duration of one journey through the mountains to the nearest train station.1936-02-276.97.00.23568078.0ReleasedSinDatoShochiku OfunaJapan1936.00.000000Hiroshi ShimizuKaoru Futaba, Michiko Kuwano, Takashi Ishiyama, Einosuke Naka, Mayumi Tsukiji, Ken Uehara
idspoken_languagesnamegenresnametitlebudgetrevenueoverviewrelease_datevote_averagevote_countpopularityruntimestatustaglineproduction_companiesnameproduction_countriesnamerelease_yearreturndirectoractor
4533699920EnglishWar, DramaConfessions of a Nazi Spy0.00.0FBI agent Ed Renard investigates the pre-War espionage activities of the German-American Bund.1939-05-065.36.00.903270104.0ReleasedTrapped!First National PicturesUnited States of America1939.00.000000Anatole LitvakEdward G. Robinson, Francis Lederer, George Sanders, Paul Lukas, Henry O'Neill, Dorothy Tree, Lya Lys, Grace Stafford, James Stephenson, Hedwiga Reicher, Joe Sawyer, Sig Ruman, Lionel Royce, Henry Victor, Hans Heinrich von Twardowski, Wolfgang Zilzer, Frederick Vogeding, Willy Kaufman, Rudolph Anders, Wilhelm von Brincken, George Rosener, Frederick Burton, Eily Malyon, Bodil Rosing, John Deering, Louis Adlon, Fred Aldrich, Sherwood Bailey, Ward Bond, Walter Bonn, Egon Brecher, Tommy Bupp, Glen Cavender, John Conte, Alec Craig, Jimmie Dundee, Jack Egger, Frederick Giermann, Lisa Golm, Sol Gorss, William Gould, Fred Graham, Creighton Hale, John Harron, Eddie Hart, Adolf Hitler, Max Hoffman Jr., Stuart Holmes, Arthur Stuart Hull, Selmer Jackson, Edward Keane, Robert Emmett Keane, Milton Kibbee, Martin Kosleck, Frank Mayo, Lon McCallister, Ray Miller, Walter Miller, Jack Mower, George Offerman Jr., Lotte Palfi Andor, Steve Pendleton, Gil Perkins, Norman Phillips Jr., Tempe Pigott, Lucien Prival, Otto Reichow, John Ridgely, Ferdinand Schumann-Heink, Hans Schumm, Lester Sharpe, Charles Sherlock, Edwin Stanley, Rudolf Steinboeck, Robert R. Stephenson, Regis Toomey, Frederic Tozere, Charles Trowbridge, Emmett Vogan, Dave Wengren, John Hamilton
4533799922EnglishWar, Adventure, DramaDirigible0.00.0Dirigible commander Jack Braden and Navy pilot 'Frisky' Pierce fight over the glory associated with a successful expedition to the South Pole and the love of beautiful Helen, Frisky's wife. After Braden's dirigible expedition fails, Frisky tries an expedition by plane. Unfortunately he crashes and strands his party at the South Pole. Braden must decide between a risky rescue attempt by dirigible and remaining safely at home with Helen.1931-04-040.01.00.078026100.0ReleasedSinDatoColumbia Pictures CorporationUnited States of America1931.00.000000Frank CapraJack Holt, Ralph Graves, Fay Wray, Hobart Bosworth, Roscoe Karns, Harold Goodwin, Clarence Muse, Emmett Corrigan, Bess Flowers, George 'Gabby' Hayes
453389993Tiếng Việt, EnglishCrime, DramaLittle Fish0.00.0Set in the Little Saigon district outside of Sydney, a woman trying to escape her past becomes embroiled in a drug deal.2005-07-195.925.04.066487114.0ReleasedThe past is right herePorchlight FilmsAustralia2005.00.000000Rowan WoodsCate Blanchett, Sam Neill, Hugo Weaving, Martin Henderson, Noni Hazlehurst, Joel Tobeck, Susie Porter, Dustin Nguyen, Lisa McCune, Nina Liu, Daniela Farinacci, Linda Cropper, Ferdinand Hoang, Anh Do, Jason Chong, Natasha Beaumont, Bic Runga, Lisa Bailey, Lan Tran, Anthony Brandon Wong, Anthony Phelan, Harli Ames, Ian Roberts, Terry Serio, Steve Vella
4533999934NaNRomance, Adventure, DramaThe Flying Fleet0.00.0Six friends are to graduate the next day from the United States Naval Academy. They all hope to become aviators. When the officer of the day becomes sick, Tommy Winslow (Ramon Navarro) has to take his place, while the others go out and celebrate.1929-01-190.00.00.008084100.0ReleasedSinDatoMetro-Goldwyn-Mayer (MGM)SinDato1929.00.000000George W. HillRamon Novarro, Ralph Graves, Anita Page, Alfred Allen, Wade Boteler, Bud Geary, Sumner Getchell, Gardner James, Roscoe Karns, Claire McDowell, Edward Nugent, Carroll Nye, The Three Sea Hawks
453409994EnglishComedy, Animation, FamilyThe Great Mouse Detective14000000.038625550.0When the diabolical Professor Ratigan kidnaps London's master toymaker, the brilliant master of disguise Basil of Baker Street and his trusted sidekick Dawson try to elude the ultimate trap and foil the perfect crime.1986-07-026.9334.011.18392474.0ReleasedLondon's crime-fighting ace on his most baffling case!Walt Disney PicturesUnited States of America1986.02.758968Ron ClementsBarrie Ingham, Val Bettin, Vincent Price, Susanne Pollatschek, Candy Candido, Diana Chesney, Eve Brenner, Alan Young, Basil Rathbone, Ellen Fitzhugh, Walker Edmiston, Wayne Allwine, Tony Anselmo, Barrie Ingham, Val Bettin, Vincent Price, Susanne Pollatschek, Candy Candido, Diana Chesney, Eve Brenner, Alan Young, Basil Rathbone, Ellen Fitzhugh, Walker Edmiston, Wayne Allwine, Tony Anselmo, Barrie Ingham, Val Bettin, Vincent Price, Susanne Pollatschek, Candy Candido, Diana Chesney, Eve Brenner, Alan Young, Basil Rathbone, Ellen Fitzhugh, Walker Edmiston, Wayne Allwine, Tony Anselmo, Barrie Ingham, Val Bettin, Vincent Price, Susanne Pollatschek, Candy Candido, Diana Chesney, Eve Brenner, Alan Young, Basil Rathbone, Ellen Fitzhugh, Walker Edmiston, Wayne Allwine, Tony Anselmo
4534199946NaNComedyExit Smiling0.00.0Beatrice Lillie and Jack Pickford star in this silent comedy about the travails of a third-rate traveling theatre company.1926-11-068.52.00.20231577.0ReleasedSinDatoMetro-Goldwyn-Mayer (MGM)United States of America1926.00.000000Sam TaylorBeatrice Lillie, Jack Pickford, Doris Lloyd, DeWitt Jennings, Harry Myers, Franklin Pangborn, Tenen Holtz, Louise Lorraine, Dorothea Wolbert, Charles K. French, Dwight Frye, D'Arcy Corrigan, William Gillespie, Gus Leonard, Andy MacLennan, Carl Richards, Carl Roup, Bert Woodruff
453429995EnglishAction, Drama, CrimeTurn It Up0.00.0Trying to bootstrap his way out of Brooklyn's mean streets is Diamond, a rap musician. With his long-time pal Gage acting as his manager, he's trying to lay down a demo tape with cut-rate studio time. To pay the bills, he and Gage run drugs for "Mr. B." Inside a week, Diamond's beloved mother dies suddenly, his father appears after an absence of 12 years and wants a relationship, and his girlfriend Kia tells him she's pregnant, asking him if he's ready to be a father. Gage steals $100,000 in a multiple-felony robbery so that Diamond can record a full album, not knowing it's Mr. B's money he's taken. B wants his money, Diamond wants his music, Tia wants an answer.2000-09-065.05.01.31617986.0ReleasedHow you gonna win?New Line CinemaUnited States of America2000.00.000000Robert AdetuyiJason Statham, Vondie Curtis-Hall, Tamala Jones, John Ralston, Ja Rule, Chris Messina, Eugene Clark, Derwin Jordan, Patrice Goodman, Chang Tseng, Harry-O, Elain R. Graham, Faith Evans, Melyssa Ford, Jeff Jones, LeRoy Allen, Shinehead, DJ Skribble, Conrad Dunn, Pras, Patricia Velásquez
453439997EnglishFantasy, Action, Horror, Science FictionGabriel0.00.0Gabriel tells the story of an archangel who fights to bring light back to purgatory - a place where darkness rules - and save the souls of the city's inhabitants.2007-11-155.077.03.840024109.0ReleasedFar From GraceHILT ProductionsAustralia2007.00.000000Shane AbbessDwaine Stevenson, Jack Campbell, Erika Heynatz, Andy Whitfield, Samantha Noble, Michael Piccirilli, Harry Pavlidis, Kevin Copeland, Matt Hylton Todd, Amy Mathews, Valentino del Toro, Goran D. Kleut, Brendan Clearkin, Christian Clark, Amber Gokken, Az Jackson, Johan Earl, Denai Gracie, Richard Huggett, Aaron Scully
4534499977EnglishComedyHot Stuff0.00.0When a police department's burglary task force is facing the possibility of being shut down because of their low conviction rate decides to try a new approach to apprehending their targets. They take over a pawn shop where thieves go to unload their merchandise. They record them as they bring stuff in and get them to tell them where they got it. Eventually they're threatened by the mob.1979-08-107.86.00.21577891.0ReleasedYou can't turn this mob over to the cops. They are the cops.Rastar PicturesSinDato1979.00.000000Dom DeLuiseDom DeLuise, Suzanne Pleshette, Jerry Reed, Ossie Davis, Luis Ávalos, Pat McCormick, Peter DeLuise
453459999Français, DeutschDrama, CrimeThe Free Will0.00.0After nine years in psychiatric detention Theo, who has brutally assaulted and raped three women, is released. Living in a supervised community, he connects well with his social worker Sascha, finds a job at a print shop and even a girlfriend, Nettie, his principal's brittle and estranged daughter. But even though superficially everything seems to work out Theo's seething rage remains ready to erupt.2006-08-236.611.01.038858163.0ReleasedSinDatoColonia MediaGermany2006.00.000000Matthias GlasnerJürgen Vogel, Sabine Timoteo, André Hennicke, Manfred Zapatka, Judith Engel, Maya Bothe, Anna Brass, Anne-Kathrin Golinsky, Anna De Carlo, Frank Wickermann, Bernadette Büllmann, Marcel Batangtaris, Andreas Laurenz Maier